80 lines
1.8 KiB
Markdown
80 lines
1.8 KiB
Markdown
# Distributed Computing
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HOWTO Set up and run Tensorflow on multiple nodes.
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This is to this particular configuration.
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# Software
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Main software in use:
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* Debian
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* Proxmox
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* Ceph
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* Python 3
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* Tensorflow
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* Jupyter
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* `clusterssh`
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# Installation
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Major steps.
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1. Install Proxmox on bare metal.
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1. Clone Debian KVM Nodes.
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1. Set up nodes.
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1. Install Tensorflow.
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1. Set up Ceph.
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## Proxmox
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Setting up Proxmox is outside the scope of this document.
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All you really need is some virtual machines, however
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they are created.
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* https://www.proxmox.com/en/proxmox-ve
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## Set up nodes
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```
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# On main workstation or node where you built tensorflow:
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NODES="ml1 ml2 ml3 ml4 ml5"
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for i in $NODES
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do scp -p tensorflow-2.1.0-cp37-cp37m-linux_x86_64.whl $i:
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done
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```
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```
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# On worker nodes:
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sudo apt update
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sudo apt install python3-pip sshfs
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# XXX deps...
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pip3 install --upgrade setuptools
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pip3 install --user tensorflow-2.1.0-cp37-cp37m-linux_x86_64.whl
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pip3 install --user simplejson
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pip3 install --user pillow
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```
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Another way, using upstream tensorflow packages.
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You also have to install the latest `pip` from `pip`,
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or you'll get `tensorflow 1.x`.
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```
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pip3 install pip
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pip3 install --upgrade pip
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# make sure new `pip3` at `~/.local/bin/pip3` is in front in `$PATH`.
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# install tensorflow
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pip3 install --user tensorflow
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# If that fails due to the PATH, run like:
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~/.local/bin/pip3 install --user tensorflow
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pip3 list | grep tensorflow
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# There's a bunch of tests that can be run, such as:
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python3 ~/devel/tensorflow/tensorflow/tensorflow/python/distribute/multi_worker_continuous_run_test.py
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```
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# Usage
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`top`
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# Meh
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```
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# for running some tensorflow tests:
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pip3 install --user portpicker
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# For other examples/tests:
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#pip3 install --user opencv-python
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apt install python3-opencv
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pip3 install --user pandas
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```
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